Technical advancements have led to miniaturization of electronic components today. This, has led to the embedding of intelligence into devices or 'things' to make them smarter Who could have envisaged the many uses of a simple phone in its smartphone avatar today? As modern compute architectures and data communication models begin to emerge; the sheer variety, velocity and volume of data we can store and process is also growing in leaps and bounds. These newer IT infrastructure models have not only led to aggregating humongous amounts of data but also led to the implementation of statistical models for predictive and prescriptive analytics for business and community benefits. As these models evolve, the context for the data processing becomes increasingly relevant, especially in the areas of Information security and corporate trust. Together with the proliferation of miniaturization in electronic components, the acceleration of advanced computing models and superior data communication systems; the Internet of Things will play a pivotal role in datacenter transformation. As the smarter world begins to witness these transformations, technologists will continue to have an increasing role in gauging these developments to create the IoT- ready datacenter of the future.

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Creating IoT-Ready Datacenters of the Future

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The IoT-Driven Smart World & Its Impact on the Datacenters
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What is Internet of Things (IoT)?
• We see IoT as billions of smart, connected things
• A sort of universal global neural network in the cloud that
will encompass every aspect of our lives
• IoT comprises of smart machines - interacting and
communicating with the other machines, objects,
environments, and infrastructure
What makes IoT Smart and how will it Impact Datacenters?
• The IoT-enabled products employ embedded technology that allows them
to communicate, directly or indirectly with each other on the Internet
• As the number of IoT devices increases and applications utilizing their data
grows exponentially, the datacenter is impacted the most.
• With this increase in quantity of data, businesses are trying to apply various
software models to understand and act upon this data.

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Architectural Elements of IoT: Three Key Paradigms
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Things-oriented
(Sensors)
Internet-oriented
(Middleware)
Semantic-oriented
(Knowledge)
Sensing nodes or sensors are devices for environmental data aggregation. Device
control, supervisory and data aggregation are primary areas of discussion in this
paradigm, as it addresses the objects‘ purpose to sense its environment and
aggregate data
Sensing nodes or sensors are devices for environmental data aggregation.
Device control, supervisory and data aggregation are primary areas of discussion
in this paradigm, as it addresses the objects‘ purpose to sense its environment
and aggregate data
This paradigm encompasses systems and infrastructure to enable data retention
for deriving business value. Typical components involved include gateway,
network and the datacenter
The primary purpose of data aggregation is to derive business value by
analyzing trends and deriving insights. In essence, cloud and business logic
become the crux of this layer

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Use Case 1: Healthcare
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Sensors
• Infusion pump, a medical device that delivers fluids to patients, including nutrients and
medications (such as insulin, hormones or chemotherapy drugs)
• It can be used to administer medication electronically in preset controlled amounts and
in a timely manner - based on real-time diagnostics of patient health monitoring data
from sensors.
Middleware
• Devices or nodes will need to be connected and interoperable in order to realize the
benefits of networking intelligent devices and enabling them to share patient data
• This helps healthcare professionals understand and correlate patients’ chronic conditions
and make accurate, timely and realistic recommendation
Semantics
• Cloud-connected smart devices provide healthcare professionals with real time patient
information and visibility to better understand the patients’ conditions and make
accurate, timely and realistic recommendations.

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Use Case 2: Aerospace and Defense
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Sensors
• Unmanned Aerial Vehicles or UAVs use complex payloads to perform intelligent
surveillance and reconnaissance.
• Rather than simply being remote controlled devices, UAVs are evolving to become
autonomous decision making entities, based on data from their own payload sensors as
well as from the other nearby entities
Middleware
• Military systems leverage Network Functions Virtualization (NFV) for high-performance
and reliability.
• A trusted, reliable Data Center is required to process the petabytes of data generated in
real-time battlefield assets every hour
Semantics
• The aggregated data in military cloud can be used to derive efficiencies and manage
costs in personnel management, security asset management and security infrastructure.
• Examples – The connected battlefield, network-centric warfare, and the Global Combat
Support System.

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Use Case 3: Transportation
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Sensors
• Sensors within vehicles as well as in roadways and railway tracks can send critical
information to traffic control sites and operators for efficient traffic routing, congestion
management and maintenance deployment
Middleware
• Gateways within the buses or trains can help provide drivers and riders with location-
based services and Wi-Fi connectivity
• Railways around the world are adopting novel solutions and techniques such as wireless
signaling, control systems, collision elimination and congestion tracking to ensure safety
Semantics
• Cloud-based communication enables operators to utilize equipment, tracks and stations
more efficiently while dramatically reducing the risk of accidental collisions
• The cloud based central control systems provide real-time equipment tracking, which
alerts operators to the location of any piece of equipment at any time and much more.

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Impact of IoT on the Datacenter
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The IoT ecosystem will definitely
impact the datacenter as more data,
sciences-related activities are leveraged
to make business work better
The analyst firm Gartner also estimates
that the IoT will comprise 26 billion units
by 2020 and expects incremental revenue
generated from these devices to be in
excess of US$ 300 billion
The Unified framework will need to
provide options/choices for real time
responses that stakeholder/business owners
demand in every aspect - be it sales,
marketing, engineering, operations, finance
or any other business function
Therefore, the need for a single
unified framework for enabling
data/information storage, processing
and actionable analytics/insights from
massive data sets becomes
increasingly evident
Datacenters need to be equipped to
handle disparate platforms, varying
amounts of data and capability to
process the same in real time for
decision making

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Effect of IoT adoption on Datacenter Components
Storage
Management
Network &
Security
Asset
Management
Audit & SLA’s
• Exceedingly large
data
• Dynamic growth
support
• Determination of
speed & IOPS of
operations
• Need to encompass a
larger stream of devices
both within the
datacenter and externally
• Collaboration among
more sets of domain-
specific users
• Value addition through
IoT domain expertise
• Securing sensor data
traversing wireless
networks
• Need for robust Internal
Networks
• Ability to manage
dynamic loads on
network mainly due to
analytics of large data
• Increasing complexity
• Endless possibilities of
end user plugging
their own devices
• Regular monitoring of
home area network ,
branch office & on-site
data

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Leveraging Datacenter Management Expertise:
The Cornerstone of IoT Success
They can help determine the
options that can be explored
for effective utilization of the
IoT technologies - at both the
infrastructure and the
business levels
Public cloud platforms such as
AWS and Azure that offer the IoT
platform services, provide
immense value to clients with
their built-in APIs and a
standardized structure of
operations that can be
implemented within an
organization
The critical part of the IoT
deployment is neither the data
nor the devices, but the way in
which the data is utilized by the
businesses in real time
A strong methodology
leverages a structured
approach to analysis, design,
deployment, and management,
allowing inclusion of the IoT
parameters at both, the
analysis and the operations
layer
Success of IoT
ecosystem

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Creating IoT-ready
Datacenters of the
Future
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